Triple
T16576526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | T2 |
E402725
|
entity |
| Predicate | hasAirlineOperationsType |
P62766
|
FINISHED |
| Object | passenger |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: passenger | Statement: [T2, hasAirlineOperationsType, passenger]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAirlineOperationsType Context triple: [T2, hasAirlineOperationsType, passenger]
-
A.
hasAircraftOperationsType
Indicates the specific category or type of aircraft operations associated with an entity, such as commercial, military, or private use.
-
B.
airlineOperationsType
chosen
Indicates the type or category of operational activities an airline conducts (e.g., passenger, cargo, charter, or mixed services).
-
C.
hasAirlines
Indicates that one entity (such as an airport, city, or country) is served by or associated with one or more airline operators.
-
D.
aircraftOperationType
Indicates the specific manner or purpose for which an aircraft is being operated (e.g., commercial, private, military, training).
-
E.
servesAirlineType
Indicates that a service provider (such as an airport, terminal, or facility) accommodates or operates flights for a specified type or category of airline.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d88387363c8190a97a0c942130de97 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3595dd90881909933216bd12505e1 |
completed | April 18, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69e296a7d9d0819088555bca6c936e79 |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:16 a.m.